Coordinate Complex AI Tasks: Design agents capable of managing intricate tasks like multi-database SQL queries or automated workflows.
Implement Intelligent Constraints: Create constraints to guide user interactions with LLMs, ensuring alignment with task objectives.
Team Collaboration: Participate in meetings with stakeholders to understand workflows, providing insights, and educating teams on LLM capabilities and limitations.
Prompt Design: Craft creative LLM prompts to guide the model toward specific tasks, ensuring alignment with desired outcomes.
Software Development: Construct robust software solutions to process LLM responses and enable seamless integration with existing applications.
Meeting Participation: Actively engage in design meetings, standups, and planning sessions to collaboratively develop and deliver solutions.
From 2 to 4 years of experience as an AI
Developer.
Expertise in Large Language Models: Experience working with state-of-the-art LLMs like GPT-4, Llama 2, and other open-source models.
Technical Skills: Proficiency in Python or C# and adeptness in modern development environments, including Git, Anaconda, PIP, Docker, and Cloud services.
Data Engineering Skills: Experience working with Semantic Kernel, LangChain, and VectorDB.
Prompt Engineering: Hands-on experience in prompt engineering to guide LLMs effectively.
Application Development: Demonstrable skills in developing LLM-based applications such as chatboxes, virtual assistants, and virtual agents
Up-to-date Knowledge: Must be current with the latest technologies, frameworks, and news in LLM and AI.
Production-Grade Coding: Ability to develop production-ready standalone libraries, going beyond typical "notebook code."
Problem-Solving and Communication: Individual contributor mindset with robust problem-solving and communication skills.
Previous Work: Must be able to share previous work with LLM interfaces and code repositories during the interview process.
Language: Fluent in English (both verbal and written).